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» Informed Selection of Training Examples for Knowledge Refine...
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87
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ECML
2006
Springer
15 years 3 months ago
Active Learning with Irrelevant Examples
Abstract. Active learning algorithms attempt to accelerate the learning process by requesting labels for the most informative items first. In real-world problems, however, there ma...
Dominic Mazzoni, Kiri Wagstaff, Michael C. Burl
IJCNN
2008
IEEE
15 years 6 months ago
Two-level clustering approach to training data instance selection: A case study for the steel industry
— Nowadays, huge amounts of information from different industrial processes are stored into databases and companies can improve their production efficiency by mining some new kn...
Heli Koskimäki, Ilmari Juutilainen, Perttu La...
81
Voted
ATAL
2008
Springer
15 years 1 months ago
An adaptive and customizable feedback system for VR-based training simulators
This paper describes a proposal to build an intelligent feedback selection system for Virtual Reality-based training simulators. The system is aimed at generating multimodal feedb...
Maite Lopez-Garate, Alberto Lozano-Rodero, Luis M....
73
Voted
DAC
2004
ACM
16 years 19 days ago
Abstraction refinement by controllability and cooperativeness analysis
ion Refinement by Controllability and Cooperativeness Analysis Freddy Y.C. Mang and Pei-Hsin Ho Advanced Technology Group, Synopsys, Inc. {fmang, pho}@synopsys.com nt a new abstrac...
Freddy Y. C. Mang, Pei-Hsin Ho
87
Voted
ESANN
2000
15 years 1 months ago
A new information criterion for the selection of subspace models
The problem of model selection is considerably important for acquiring higher levels of generalization capability in supervised learning. In this paper, we propose a new criterion ...
Masashi Sugiyama, Hidemitsu Ogawa